CD8 T cells mediate aortic allograft vasculopathy by direct killing and an interferon-?-dependent indirect pathway
Bibliographic record
Abstract
OBJECTIVE: Allograft vasculopathy (AV) has emerged as the major obstacle to long-term survival in clinical heart transplantation. Immune events are implicated in the development of AV, but the cellular and molecular mechanisms involved remain unclear. We sought to determine whether and by what mechanism CD8(+) T lymphocytes are able to generate AV in a murine aortic allograft model. METHODS: Allo-primed CD8(+) T lymphocytes were transferred into immunodeficient (RAG-1(-/-)) mouse recipients of aortic allografts. We also transferred primed CD8(+) T cells with targeted deletions of effector molecules (perforin, Fas-ligand) to determine the role of direct cytolysis (CTL) in CD8(+) T-cell-mediated AV. We determined the role of non-CTL effector mechanisms through the transfer of either wildtype or interferon-gamma (IFN-gamma)-deficient CD8(+) T cells into RAG-1(-/-) recipients of MHC class I-deficient allografts. RESULTS: Adoptive transfer of primed wildtype CD8(+) T lymphocytes into immunodeficient recipients of aortic allografts resulted in the development of robust AV lesions. Transfer of CD8(+) T lymphocytes with targeted deletions in CTL effector molecules resulted in reduction of AV lesion size but not abrogation. Transfer of wildtype CD8(+) T cells into recipients of MHC class I-deficient grafts resulted in a reduction in AV lesion size, while transfer of interferon-gamma-deficient CD8(+) T cells into MHC class I-deficient grafts abrogated AV. CONCLUSIONS: These data indicate that CD8(+) T cells mediate AV through direct cytolysis and a distinct interferon-gamma-dependent non-CTL effector pathway. Given the resistance of this cell type to conventional immunosuppression, these results may have important therapeutic implications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".